{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt \n",
    "\n",
    "from matplotlib.font_manager import FontManager\n",
    "fm = FontManager()\n",
    "mat_fonts = set(f.name for f in fm.ttflist) \n",
    "\n",
    "plt.rcParams['font.sans-serif'] = 'Kaiti'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>男1000米跑</th>\n",
       "      <th>男1000米跑分数</th>\n",
       "      <th>男50米跑</th>\n",
       "      <th>男50米跑分数</th>\n",
       "      <th>男跳远</th>\n",
       "      <th>男跳远分数</th>\n",
       "      <th>男体前屈</th>\n",
       "      <th>男体前屈分数</th>\n",
       "      <th>男引体</th>\n",
       "      <th>男引体分数</th>\n",
       "      <th>男肺活量</th>\n",
       "      <th>男肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.13</td>\n",
       "      <td>72</td>\n",
       "      <td>8.88</td>\n",
       "      <td>66</td>\n",
       "      <td>195</td>\n",
       "      <td>60</td>\n",
       "      <td>12</td>\n",
       "      <td>74</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2785</td>\n",
       "      <td>62</td>\n",
       "      <td>170</td>\n",
       "      <td>72.599998</td>\n",
       "      <td>25.120001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.16</td>\n",
       "      <td>70</td>\n",
       "      <td>7.70</td>\n",
       "      <td>78</td>\n",
       "      <td>225</td>\n",
       "      <td>74</td>\n",
       "      <td>11</td>\n",
       "      <td>74</td>\n",
       "      <td>7</td>\n",
       "      <td>60</td>\n",
       "      <td>3133</td>\n",
       "      <td>68</td>\n",
       "      <td>174</td>\n",
       "      <td>52.700001</td>\n",
       "      <td>17.410000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.09</td>\n",
       "      <td>74</td>\n",
       "      <td>8.45</td>\n",
       "      <td>70</td>\n",
       "      <td>218</td>\n",
       "      <td>70</td>\n",
       "      <td>14</td>\n",
       "      <td>78</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3901</td>\n",
       "      <td>80</td>\n",
       "      <td>169</td>\n",
       "      <td>46.500000</td>\n",
       "      <td>16.280001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.21</td>\n",
       "      <td>68</td>\n",
       "      <td>8.05</td>\n",
       "      <td>74</td>\n",
       "      <td>206</td>\n",
       "      <td>64</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4946</td>\n",
       "      <td>100</td>\n",
       "      <td>183</td>\n",
       "      <td>79.699997</td>\n",
       "      <td>23.799999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>3.44</td>\n",
       "      <td>85</td>\n",
       "      <td>7.52</td>\n",
       "      <td>78</td>\n",
       "      <td>210</td>\n",
       "      <td>66</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>9</td>\n",
       "      <td>68</td>\n",
       "      <td>3538</td>\n",
       "      <td>74</td>\n",
       "      <td>171</td>\n",
       "      <td>54.700001</td>\n",
       "      <td>18.709999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   班级 性别  男1000米跑  男1000米跑分数  男50米跑  男50米跑分数  男跳远  男跳远分数  男体前屈  男体前屈分数  男引体  \\\n",
       "0   1  男     4.13         72   8.88       66  195     60    12      74    1   \n",
       "1   1  男     4.16         70   7.70       78  225     74    11      74    7   \n",
       "2   1  男     4.09         74   8.45       70  218     70    14      78    1   \n",
       "3   1  男     4.21         68   8.05       74  206     64    13      76    1   \n",
       "4   1  男     3.44         85   7.52       78  210     66    13      76    9   \n",
       "\n",
       "   男引体分数  男肺活量  男肺活量分数   身高         体重        BMI  \n",
       "0      0  2785      62  170  72.599998  25.120001  \n",
       "1     60  3133      68  174  52.700001  17.410000  \n",
       "2      0  3901      80  169  46.500000  16.280001  \n",
       "3      0  4946     100  183  79.699997  23.799999  \n",
       "4     68  3538      74  171  54.700001  18.709999  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>女800米跑</th>\n",
       "      <th>女800米跑分数</th>\n",
       "      <th>女50米跑</th>\n",
       "      <th>女50米跑分数</th>\n",
       "      <th>女跳远</th>\n",
       "      <th>女跳远分数</th>\n",
       "      <th>女体前屈</th>\n",
       "      <th>女体前屈分数</th>\n",
       "      <th>女仰卧</th>\n",
       "      <th>女仰卧分数</th>\n",
       "      <th>女肺活量</th>\n",
       "      <th>女肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.22</td>\n",
       "      <td>100</td>\n",
       "      <td>9.32</td>\n",
       "      <td>72</td>\n",
       "      <td>185</td>\n",
       "      <td>85</td>\n",
       "      <td>16</td>\n",
       "      <td>76</td>\n",
       "      <td>48</td>\n",
       "      <td>85</td>\n",
       "      <td>3775</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>51.299999</td>\n",
       "      <td>19.309999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>4.59</td>\n",
       "      <td>40</td>\n",
       "      <td>11.44</td>\n",
       "      <td>10</td>\n",
       "      <td>148</td>\n",
       "      <td>60</td>\n",
       "      <td>9</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>66</td>\n",
       "      <td>3683</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>66.599998</td>\n",
       "      <td>25.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.46</td>\n",
       "      <td>80</td>\n",
       "      <td>13.40</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>7</td>\n",
       "      <td>64</td>\n",
       "      <td>40</td>\n",
       "      <td>76</td>\n",
       "      <td>3331</td>\n",
       "      <td>100</td>\n",
       "      <td>157.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>24.340000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.39</td>\n",
       "      <td>85</td>\n",
       "      <td>9.52</td>\n",
       "      <td>70</td>\n",
       "      <td>172</td>\n",
       "      <td>76</td>\n",
       "      <td>21</td>\n",
       "      <td>90</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>3701</td>\n",
       "      <td>100</td>\n",
       "      <td>160.0</td>\n",
       "      <td>50.700001</td>\n",
       "      <td>19.799999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.43</td>\n",
       "      <td>80</td>\n",
       "      <td>9.79</td>\n",
       "      <td>68</td>\n",
       "      <td>145</td>\n",
       "      <td>50</td>\n",
       "      <td>8</td>\n",
       "      <td>64</td>\n",
       "      <td>34</td>\n",
       "      <td>70</td>\n",
       "      <td>3592</td>\n",
       "      <td>100</td>\n",
       "      <td>167.0</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>22.910000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   班级 性别  女800米跑  女800米跑分数  女50米跑  女50米跑分数  女跳远  女跳远分数  女体前屈  女体前屈分数  女仰卧  \\\n",
       "0   1  女    3.22       100   9.32       72  185     85    16      76   48   \n",
       "1   1  女    4.59        40  11.44       10  148     60     9      66   29   \n",
       "2   1  女    3.46        80  13.40        0  150     60     7      64   40   \n",
       "3   1  女    3.39        85   9.52       70  172     76    21      90   46   \n",
       "4   1  女    3.43        80   9.79       68  145     50     8      64   34   \n",
       "\n",
       "   女仰卧分数  女肺活量  女肺活量分数     身高         体重        BMI  \n",
       "0     85  3775     100  163.0  51.299999  19.309999  \n",
       "1     66  3683     100  163.0  66.599998  25.070000  \n",
       "2     76  3331     100  157.0  60.000000  24.340000  \n",
       "3     85  3701     100  160.0  50.700001  19.799999  \n",
       "4     70  3592     100  167.0  63.900002  22.910000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#导入数据\n",
    "boys = pd.read_excel('./体测分数_男生.xls')\n",
    "girls = pd.read_excel('./体测分数_女生.xls')\n",
    "display(boys.head(),girls.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1、对男1000米跑、男引体 进行等宽分箱操作，分成3分，并使用饼图绘制百分比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '          男1000米跑分数分布         ')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#男1000米跑，等宽分箱操作\n",
    "pd.cut(boys['男1000米跑分数'],\n",
    "       bins = 3,\n",
    "       labels = ['不及格','中等','优秀'],\n",
    "       right = True)\n",
    "boys['等级1'] = pd.cut(boys['男1000米跑分数'],\n",
    "                      bins = [0,60,80,100],\n",
    "                      labels = ['不及格','中等','优秀'])\n",
    "\n",
    "run = boys['等级1'].value_counts()\n",
    "\n",
    "plt.figure(figsize = (6,6))\n",
    "_ = plt.pie(run,\n",
    "            labels = run.index,\n",
    "            textprops = {'family':'FangSong','fontsize':18},\n",
    "            autopct = '%0.2f%%',#显示标签：百分比\n",
    "            wedgeprops={'width':0.5},#圆环\n",
    "            pctdistance=0.7) #字体居中\n",
    "plt.title(label = '          男1000米跑分数分布         ',fontsize = 24,pad = 20)\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '          男引体分数分布         ')"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#男引体，等宽分箱操作\n",
    "pd.cut(boys['男引体分数'],\n",
    "       bins = 3,\n",
    "       labels = ['不及格','中等','优秀'],\n",
    "       right = True)\n",
    "boys['等级2'] = pd.cut(boys['男引体分数'],\n",
    "                      bins = [0,60,80,100],\n",
    "                      labels = ['不及格','中等','优秀'])\n",
    "\n",
    "yt = boys['等级2'].value_counts()\n",
    "\n",
    "plt.figure(figsize = (6,6))\n",
    "_ = plt.pie(yt,\n",
    "            labels = run.index,\n",
    "            textprops = {'family':'FangSong','fontsize':18},\n",
    "            autopct = '%0.2f%%',#显示标签：百分比\n",
    "            wedgeprops={'width':0.5},#圆环\n",
    "            pctdistance=0.7) #字体居中\n",
    "plt.title(label = '          男引体分数分布         ',fontsize = 24,pad = 20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2、对女800米跑，女跳远进行直方图绘制统计各分数段人数，分成4份"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#女800米跑，分数分布直方图\n",
    "girls['分数分布'] = pd.cut(girls['女800米跑分数'],\n",
    "                        bins = [0,25,50,75,100],\n",
    "                        labels=['0-25','25-50','50-75','75-100']) \n",
    "girls \n",
    "\n",
    "run = girls['分数分布'].value_counts()\n",
    "\n",
    "plt.figure(figsize = (12,9))\n",
    "plt.bar(x = run.index,\n",
    "        height= run,\n",
    "        color = plt.cm.RdBu_r(np.linspace(0,1,run.size)),\n",
    "        width = 0.5\n",
    "        )\n",
    "plt.title(label='    女800米跑分数分布    ',\n",
    "          fontsize = 32,\n",
    "          color = 'white',\n",
    "          backgroundcolor = '#c5b783',\n",
    "          weight = 'bold',\n",
    "          pad = 30)\n",
    "\n",
    "plt.grid(axis='y',color = 'k')\n",
    "plt.box(False)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#女跳远分数，分数分布直方图\n",
    "girls['分数分布'] = pd.cut(girls['女跳远分数'],\n",
    "                        bins = [0,25,50,75,100],\n",
    "                        labels=['0-25','25-50','50-75','75-100']) \n",
    "girls \n",
    "\n",
    "ty = girls['分数分布'].value_counts()\n",
    "\n",
    "plt.figure(figsize = (12,9))\n",
    "plt.bar(x = ty.index,\n",
    "        height= ty,\n",
    "        color = plt.cm.RdBu_r(np.linspace(0,1,run.size)),\n",
    "        width = 0.5\n",
    "        )\n",
    "plt.title(label='    女跳远分数分布    ',\n",
    "          fontsize = 32,\n",
    "          color = 'white',\n",
    "          backgroundcolor = '#c5b783',\n",
    "          weight = 'bold',\n",
    "          pad = 30)\n",
    "\n",
    "plt.grid(axis='y',color = 'k')\n",
    "plt.box(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3、使用嵌套饼图对男女生体重指数据进行比例统计，分为正常、低体重、超重、肥胖（男女生体重指数参考如下）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x281434bd400>"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#男生体重指数比例统计\n",
    "boys['体重等级'] = pd.cut(boys['BMI'],\n",
    "                          bins = [0,16.4,23.3,26.3,100],\n",
    "                          labels = ['低体重','正常','超重','肥胖'])\n",
    "p1 = boys['体重等级'].value_counts()\n",
    "#女生体重指数比例统计\n",
    "girls['体重等级'] = pd.cut(girls['BMI'],\n",
    "                          bins = [0,16.4,22.7,25.2,100],\n",
    "                          labels = ['低体重','正常','超重','肥胖'])\n",
    "p2 = girls['体重等级'].value_counts()\n",
    "\n",
    "plt.figure(figsize=(9,9))\n",
    "_ = plt.pie(p1,\n",
    "        radius=1,\n",
    "        autopct='%0.2f%%',\n",
    "        wedgeprops={'linewidth':5,#间隔的宽度\n",
    "                   'width':0.3,#饼图的宽度\n",
    "                   'edgecolor':'white'},\n",
    "        pctdistance=0.85,\n",
    "        labels = p1.index,\n",
    "        textprops = {'family':'FangSong','fontsize':18}\n",
    "        )\n",
    "\n",
    "_ = plt.pie(p2,\n",
    "        radius=0.7,\n",
    "        autopct='%0.2f%%',\n",
    "        wedgeprops={'linewidth':5,#间隔的宽度\n",
    "                   'width':0.7,#饼图的宽度\n",
    "                   'edgecolor':'white'},\n",
    "        pctdistance= 0.55)\n",
    "\n",
    "plt.rcParams['font.family'] = 'Kaiti'\n",
    "plt.rcParams['font.size'] = 12\n",
    "plt.legend(p2.index,title = '类别',prop = 'Kaiti') #举手提问：怎么才能显示p2的图例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
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   "toc_position": {},
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